Author of the publication

Big Data Analytics for Nabbing Fraudulent Transactions in Taxation System.

, , , , , and . BigData, volume 11514 of Lecture Notes in Computer Science, page 95-109. Springer, (2019)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

 

Other publications of authors with the same name

A Novel Example-Dependent Cost-Sensitive Stacking Classifier to Identify Tax Return Defaulters., , , , , and . BIS, page 343-353. (2021)Big Data Analytics for Tax Administration., , , , , , , and . EGOVIS, volume 11709 of Lecture Notes in Computer Science, page 47-57. Springer, (2019)Link prediction techniques to handle tax evasion., , , and . COMAD/CODS, page 307-315. ACM, (2021)Curtailing the Tax Leakages by Nabbing Return Defaulters in Taxation System., , , , and . AusDM, volume 1127 of Communications in Computer and Information Science, page 183-195. Springer, (2019)Predictive Modeling for Identifying Return Defaulters in Goods and Services Tax., , , , and . DSAA, page 631-637. IEEE, (2018)Clustering Collusive Dealers in Commercial Taxation System., , , and . IntelliSys (2), volume 869 of Advances in Intelligent Systems and Computing, page 703-717. Springer, (2018)Big Data Analytics for Nabbing Fraudulent Transactions in Taxation System., , , , , and . BigData, volume 11514 of Lecture Notes in Computer Science, page 95-109. Springer, (2019)Detecting Tax Evaders Using TrustRank and Spectral Clustering., , , , , and . BIS, volume 389 of Lecture Notes in Business Information Processing, page 169-183. Springer, (2020)DeepCatch: Predicting Return Defaulters in Taxation System using Example-Dependent Cost-Sensitive Deep Neural Networks., , , and . IEEE BigData, page 4412-4419. IEEE, (2020)An algorithmic approach to handle circular trading in commercial taxing system., , , and . CoRR, (2017)